single file

W.. moment based image normalization, a well-known technique in computer vision and pattern recognition applications [10]. In this approach both watermark embedding and extraction

The obtained results were quite positive for the first methodology which considers a classi- caly approach of classification, using diverse features extracted from the texts in order

In order to achieve robustness, a crucial property for a reliable automatic system, we opted for a multi-cue approach, using raw pixels as global descriptors and SIFT features as

For the visual features we adopt an existing approach for search based classification using content based image retrieval on global features with feature selection and

Secondly, unlike the feature-based approach where the online classification is merely based on extracting certain features from the input SAR chip and determining where the

Three main steps compose this approach: (1) projection of data in a new space of time series related features (e.g. derivated), (2) estima- tion of the density of known normal

In the experi- mental section, we evaluate the proposed kernel using SIFT features adapted to time series [2, 7] and show that it significantly outperforms the original algorithm

It can be seen in Equation (3) that the extracted features are structured. Distance features tell how well a shapelet matches a time series, while localization features inform about